Description
We're looking for an Agentic AI Engineer to design and ship autonomous agents that connect to enterprise data and turn natural-language questions into trustworthy, cited answers.
You'll build and productionize reusable agentic components, take AI models and agents from prototype to production, and improve how agents reason.
Responsibilities:
- Build and productionize reusable agentic components , skills, orchestration workflows, and tool-calling integrations , that plug into OneAI's intelligence layer (Neo4j + pgvector + Databricks + Claude).
- Take AI models and agents from prototype to production, and keep them healthy once they're live.
- Improve how agents reason: prompt design, memory and context management, retrieval quality, and multi-step tool use.
- Tune for latency, reliability, and cost so the platform holds up as more teams rely on it.
- Partner with product managers and data engineers to shape what we build, and share what you learn with the team.
- Help raise the bar on evaluation , measure solve rates and accuracy, and use what you find to make the agents better.
Requirements:
- Around 3+ years building AI/ML or backend systems, including some experience running LLM-powered services in production.
- Strong fundamentals in Python and REST APIs.
- Familiarity with modern AI tooling , frameworks like LangChain or LlamaIndex, and vector databases.
- A habit of measuring quality and iterating, rather than shipping and hoping.
- Comfort working with cloud platforms (AWS, GCP, or Azure) and containers (Docker, Kubernetes).
Nice to have:
- Experience with event streaming (Kafka, Flink, or Kinesis) and data pipelines (Spark or Databricks).
- Exposure to production operations , CI/CD, monitoring, alerting, and incident response.
- Interest in AI governance, safety, or evaluation.
The expected pay range for this position is $139,000 - $257,550 annually.